Conocimiento, percepción y formación en inteligencia artificial: análisis de moderación en docentes universitarios mexicanos

Alonso Contreras Avila; Myrna Delfina López Noriega; Lorena Zalthen Hernández

doi:10.31637/epsir-2026-2178

Authors

Alonso Contreras Avila Universidad Autónoma del Carmen https://orcid.org/0000-0002-2943-4836
Myrna Delfina López Noriega Universidad Autónoma del Carmen https://orcid.org/0000-0003-1426-8406
Lorena Zalthen Hernández Universidad Autónoma del Carmen https://orcid.org/0000-0002-6311-8052

DOI:

https://doi.org/10.31637/epsir-2026-2178

Keywords:

artificial intelligence, faculty training, perception, higher education, technological knowledge, teacher attitude, digital education, technology adoption

Abstract

Introduction: Artificial intelligence (AI) is transforming higher education, yet its impact depends on faculty knowledge and attitudes. This study examines whether perception/attitude toward AI (PIA) moderates the relationship between faculty training in AI (FIA) and knowledge of this technology. Methodology: A quantitative, non-experimental, cross-sectional, and correlational-explanatory approach was used. A total of 153 university faculty members responded to the validated CAPIAG-P questionnaire, which assesses three dimensions: knowledge, perception/attitude, and training. Statistical analysis included linear regression with interaction. Results: The model explained 37,08% of the variance in knowledge. Training in AI (FIA) showed a non-significant positive effect (β = 0,24, p = 0,501), while perception/attitude (PIA) had a non-significant negative effect (β = -0,29, p = 0,425). The FIA × PIA interaction was also not significant (β = 0,16, p = 0,150). Discussions: Results suggest that although AI training may influence faculty knowledge, this effect is not moderated by attitude. Initial perceptions neither strengthen nor weaken this relationship. Conclusions: It is essential to promote technical training programs in AI for faculty members, regardless of their initial attitudes toward this technology.

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Author Biographies

Alonso Contreras Avila, Universidad Autónoma del Carmen

Doctor of Management Sciences, Master of Finance and Bachelor of Marketing from the Autonomous University of Carmen. He currently works as a professor in the Faculty of Economic and Administrative Sciences at the Autonomous University of Carmen and is a member of the Academic Body for Innovation in Organisations and the Academy of Statistics. He has been appointed as a candidate in the National System of Researchers and Investigators of CONAHCYT.

Myrna Delfina López Noriega, Universidad Autónoma del Carmen

Doctor of Administration, Master of Administration, and Architect. She is currently affiliated with the Autonomous University of Carmen, serving as leader of the Consolidated Academic Body for Innovation in Organisations. She is an active member of the Latin American Research Network on Organisational Competitiveness (RILCO). She is also the founder of the Network of Academic Bodies on Corporate Social Responsibility (RECARSE) and is part of the Regional Research Network (RIR), where she has developed multiple collaborative projects. Her main lines of research include social responsibility, competitiveness, business resilience, and the prospects for the Sustainable Development Goals (SDGs). Her participation in research networks has led to joint publications in the RIR and RILCO, consolidating her commitment to the generation and dissemination of knowledge in these areas.

Lorena Zalthen Hernández, Universidad Autónoma del Carmen

She holds a Master's degree in Finance and a Bachelor's degree in Business Administration. She is currently affiliated with the Autonomous University of Carmen, where she carries out her academic and research activities. She is part of the Consolidated Academic Body for Innovation in Organisations. She is a member of the Latin American Research Network on Organisational Competitiveness (RILCO) and founder of the Network of Academic Bodies on Corporate Social Responsibility (RECARSE). She is also part of the Regional Research Network (RIR), actively participating in collaborative projects. Her main lines of research cover social responsibility, competitiveness, business resilience, and the prospects for the Sustainable Development Goals (SDGs). She has contributed to various joint publications in the RIR and RILCO, strengthening academic production in these areas.

References

Abulibdeh, A., Zaidan, E. y Abulibdeh, R. (2024). Navigating the confluence of artificial intelligence and education for sustainable development in the era of industry 4.0: Challenges, opportunities, and ethical dimensions. Journal of Cleaner Production, 437, 140527, https://doi.org/10.1016/j.jclepro.2023.140527 DOI: https://doi.org/10.1016/j.jclepro.2023.140527

Airaj, M. (2024). Ethical artificial intelligence for teaching-learning in higher education. Educ Inf Technol, 29, 17145-17167. https://doi.org/10.1007/s10639-024-12545-x DOI: https://doi.org/10.1007/s10639-024-12545-x

Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211. https://doi.org/10.1016/0749-5978(91)90020-T DOI: https://doi.org/10.1016/0749-5978(91)90020-T

Aldreabi, H., Dahdoul, N., Alhur, M., Alzboun, N. y Alsalhi, N. (2025). Determinants of Student Adoption of Generative AI in Higher Education. Electronic Journal of e-Learning, 23(1),

15-33 https://doi.org/10.34190/ejel.23.1.3599 DOI: https://doi.org/10.34190/ejel.23.1.3599

Aljemely, Y. (2024). Challenges and best practices in training teachers to utilize artificial intelligence: a systematic review. Frontiers in Education. https://doi.org/10.3389/feduc.2024.1470853 DOI: https://doi.org/10.3389/feduc.2024.1470853

Al-kfairy, M., Mustafa, D., Kshetri, N., Insiew, M. y Alfandi, O. (2024). Ethical Challenges and Solutions of Generative AI: An Interdisciplinary Perspective. Informatics, 11(3),

58. https://doi.org/10.3390/informatics11030058 DOI: https://doi.org/10.3390/informatics11030058

Al-Zyoud, H. (2020). The Role of Artificial Intelligence in Teacher Professional Development. Universal Journal of Educational Research, 8(11B), 6263-6272. https://doi.org/10.13189/ujer.2020.082265 DOI: https://doi.org/10.13189/ujer.2020.082265

Baker, B., Mills, K. A., McDonald, P. y Wang, L. (2023). AI, Concepts of Intelligence, and Chatbots: The “Figure of Man,” the Rise of Emotion, and Future Visions of Education. Teachers College Record, 125(6), 60-84. https://doi.org/10.1177/01614681231191291 DOI: https://doi.org/10.1177/01614681231191291

Bayaga, A. (2024). Leveraging AI-enhanced and emerging technologies for pedagogical innovations in higher education. Educ. Inf. Technol., 30, 1045-1072. https://doi.org/10.1007/s10639-024-13122-y DOI: https://doi.org/10.1007/s10639-024-13122-y

Bura, C. y Myakala, P. (2024). Advancing Transformative Education: Generative AI as a Catalyst for Equity and Innovation. ArXiv, abs/2411.15971. https://doi.org/10.48550/arXiv.2411.15971

Chao-Rebolledo, C. y Rivera-Navarro, M. (2024). Usos y percepciones de herramientas de inteligencia artificial en la educación superior en México. Revista Iberoamericana de Educación, 95(1), 57-72. https://doi.org/10.35362/rie9516259 DOI: https://doi.org/10.35362/rie9516259

Chatterjee, S. y Bhattacharjee, K. (2020). Adoption of artificial intelligence in higher education: a quantitative analysis using structural equation modelling. Education and Information Technologies, 25, 3443-3463. https://doi.org/10.1007/s10639-020-10159-7 DOI: https://doi.org/10.1007/s10639-020-10159-7

Chou, C., Shen, T., Shen, T. y Shen, C. (2024). Teachers’ adoption of AI-supported teaching behavior and its influencing factors: using structural equation modeling. Journal of Computers in Education. https://doi.org/10.1007/s40692-024-00332-z DOI: https://doi.org/10.1007/s40692-024-00332-z

Cordero, J., Torres-Zambrano, J. y Cordero-Castillo, A. (2025). Integration of Generative Artificial Intelligence in Higher Education: Best Practices. Education Sciences, 15(1), 32. https://doi.org/10.3390/educsci15010032 DOI: https://doi.org/10.3390/educsci15010032

Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319. DOI: https://doi.org/10.2307/249008

Erdmann, A. y Toro-Dupouy, L. (2025). The influence of the institutional environment on AI adoption in universities: identifying value drivers and necessary conditions. European Journal of Innovation Management. https://doi.org/10.1108/ejim-04-2024-0407 DOI: https://doi.org/10.1108/EJIM-04-2024-0407

Ertmer, P. A. y Ottenbreit-Leftwich, A. T. (2010). Teacher Technology Change: How Knowledge, Confidence, Beliefs, and Culture Intersect. Journal of Research on Technology in Education, 42(3), 255-284. https://doi.org/10.1080/15391523.2010.10782551 DOI: https://doi.org/10.1080/15391523.2010.10782551

Fu, Y. y Weng, Z. (2024). Navigating the ethical terrain of AI in education: A systematic review on framing responsible human-centered AI practices. Computers and Education: Artificial Intelligence. https://doi.org/10.1016/j.caeai.2024.100306 DOI: https://doi.org/10.1016/j.caeai.2024.100306

Granić, A. (2022). Educational Technology Adoption: A systematic review. Education and Information Technologies, 27, 9725-9744. https://doi.org/10.1007/s10639-022-10951-7 DOI: https://doi.org/10.1007/s10639-022-10951-7

Guerrero-Quiñonez, A. J., Bedoya-Flores, M. C., Mosquera-Quiñonez, E. F., Mesías-Simisterra, Á. E. y Bautista-Sánchez, J. V. (2023). Artificial Intelligence and its scope in Latin American higher education. Ibero-American Journal of Education & Society Research, 3(1), 264-271. https://doi.org/10.56183/iberoeds.v3i1.627 DOI: https://doi.org/10.56183/iberoeds.v3i1.627

Guillén-Gámez, F. D., Ruiz-Palmero, J., Palacios Rodríguez, A. y Martín-Párraga, L. (2022). Formación del profesorado universitario en Competencia Digital: análisis con métodos de investigación correlacionales y comparativos. Hachetetepé. Revista científica en Educación y Comunicación, 24, 1-11. https://doi.org/10.25267/Hachetetepe.2022.i24.1101 DOI: https://doi.org/10.25267/Hachetetepe.2022.i24.1101

Hamal, O., El Faddouli, N. E., Harouni, M. H. A. y Lu, J. (2022). Artificial Intelligent in Education. Sustainability, 14, 2862. https://doi.org/10.3390/su14052862 DOI: https://doi.org/10.3390/su14052862

Hayes, A. F. (2022). Introduction to mediation, moderation, and conditional process analysis: a regression-based approach (3rd ed.). The Guilford Press.

Hazzan-Bishara, A., Kol, O. y Levy, S. (2025). The factors affecting teachers’ adoption of AI technologies: A unified model of external and internal determinants. Education and Information Technologies. https://doi.org/10.1007/s10639-025-13393-z DOI: https://doi.org/10.1007/s10639-025-13393-z

Herrera, P., Huepe, M. y Trucco, D. (2025). Educación y desarrollo de competencias digitales en América Latina y el Caribe, Documentos de Proyectos (LC/TS.2025/3), Santiago, Comisión Económica para América Latina y el Caribe (CEPAL).

Holmes, W., Porayska-Pomsta, K., Holstein, K., Sutherland, E., Baker, T., Shum, S., Santos, O., Rodrigo, M., Cukurova, M., Bittencourt, I. y Koedinger, K. (2021). Ethics of AI in Education: Towards a Community-Wide Framework. International Journal of Artificial Intelligence in Education, 32, 504-526. https://doi.org/10.1007/s40593-021-00239-1 DOI: https://doi.org/10.1007/s40593-021-00239-1

Holmes, W., Bialik, M. y Fadel, C. (2022). Artificial Intelligence in Education: Promises and Implications for Teaching and Learning. Center for Curriculum Redesign. http://bit.ly/AIED-BOOK DOI: https://doi.org/10.58863/20.500.12424/4276068

Howard, S. K., Tondeur, J. M. J. y Yang, J. (2021). What to teach? Strategies for developing digital competence in pre-service teacher training. Computers & Education, 165, 104149. https://doi.org/10.1016/j.compedu.2021.104149 DOI: https://doi.org/10.1016/j.compedu.2021.104149

Jaiswal, P. (2020). Integrating Educational Technologies to Augment Learners' Academic Achievements. Int. J. Emerg. Technol. Learn., 15, 145-159. https://doi.org/10.3991/ijet.v15i02.11809 DOI: https://doi.org/10.3991/ijet.v15i02.11809

Jardón Gallegos, M. del C., Allas Chisag, W. D., Zamora Valencia, D. A. y Cedeño Saltos, N. E. (2024). Impacto de la inteligencia artificial en la educación superior: percepciones de alumnos y profesores sobre el uso de IA en el aprendizaje y la evaluación. Reincisol, 3(6), 7008-7033. https://doi.org/10.59282/reincisol.V3(6)7008-7033 DOI: https://doi.org/10.59282/reincisol.V3(6)7008-7033

Kamalov, F. Santandreu Calonge, D. y Gurrib, I. (2023). New Era of Artificial Intelligence in Education: Towards a Sustainable Multifaceted Revolution. Sustainability, 15, 12451. https://doi.org/10.3390/su151612451 DOI: https://doi.org/10.3390/su151612451

Khan, M. A. (2021). COVID-19’s Impact on Higher Education: A Rapid Review of Early Reactive Literature. Education Sciences, 11(8), 421. https://doi.org/10.3390/educsci11080421 DOI: https://doi.org/10.3390/educsci11080421

López Ros, S. P., Cascales Martínez, A. y Gomariz Vicente, M. Á. (2024). Cuestionario sobre el conocimiento, actitud y percepción del profesorado hacia la inteligencia artificial generativa. CAPIAG-P (profesorado). https://digitum.um.es/digitum/handle/10201/141368

Luckin, R., Holmes, W., Griffiths, M. y Forcier, L. B. (2016). Intelligence Unleashed: An Argument for AI in Education. Pearson.

Miao, F., Holmes, W., Huang, R. y Zhang, H. (2021). AI and education: guidance for policy-makers. UNESCO Publishing. https://doi.org/10.54675/PCSP7350 DOI: https://doi.org/10.54675/PCSP7350

Ng, D. T. K., Leung, J. K. L., Su, J., Ng, R. C. W. y Chu, S. K. W. (2023). Teachers’ AI digital competencies and twenty-first century skills in the post-pandemic world. Education Tech Research Dev, 71, 137-161. https://doi.org/10.1007/s11423-023-10203-6 DOI: https://doi.org/10.1007/s11423-023-10203-6

Özdemir, O. (2024). Kahoot! Game-based digital learning platform: A comprehensive meta-analysis. J. Comput. Assist. Learn., 41. https://doi.org/10.1111/jcal.13084 DOI: https://doi.org/10.1111/jcal.13084

Parker, J., Richard, V., Acabá, A., Escoffier, S., Flaherty, S., Jablonka, S. y Becker, K. (2024). Negotiating Meaning with Machines: AI's Role in Doctoral Writing Pedagogy. International Journal of Artificial Intelligence in Education. https://doi.org/10.1007/s40593-024-00425-x DOI: https://doi.org/10.2139/ssrn.4793715

Petko, D., Cantieni, A. y Prasse, D. (2017). Perceived Quality of Educational Technology Matters. Journal of Educational Computing Research, 54, 1070-1091. https://doi.org/10.1177/0735633116649373 DOI: https://doi.org/10.1177/0735633116649373

Salas-Pilco, S. Z., Xiao, K. y Hu, X. (2022). Artificial Intelligence and Learning Analytics in Teacher Education: A Systematic Review. Education Sciences, 12(8), 569. https://doi.org/10.3390/educsci12080569 DOI: https://doi.org/10.3390/educsci12080569

Secretaría de Educación Pública. (2020). Agenda digital educativa mexicana. https://acortar.link/CHzisL

Sharma, L. y Srivastava, M. (2019). Teachers’ motivation to adopt technology in higher education. Journal of Applied Research in Higher Education. https://doi.org/10.1108/JARHE-07-2018-0156 DOI: https://doi.org/10.1108/JARHE-07-2018-0156

Socorro Ovalles, J. A. (2024). Actitudes del profesorado ante el uso y manejo de la inteligencia artificial generativa (IAG) de modo eficiente. Revista Científica De Salud y Desarrollo Humano, 5(3), 1183-1213. https://doi.org/10.61368/r.s.d.h.v5i3.325 DOI: https://doi.org/10.61368/r.s.d.h.v5i3.325

Tan, X., Cheng, G. y Ling, M. (2024). Artificial Intelligence in Teaching and Teacher Professional Development: A Systematic Review. Computers and Education: Artificial Intelligence. https://doi.org/10.1016/j.caeai.2024.100355 DOI: https://doi.org/10.1016/j.caeai.2024.100355

Tarisayi, K. (2024). Preparing For AI’s Transformational Potential: Rethinking Teacher Education In South Africa. International Education Trend Issues, 2(1), 31-40. https://doi.org/10.56442/ieti.v2i1.364 DOI: https://doi.org/10.56442/ieti.v2i1.364

Teo, T. (2011). Factors influencing teachers’ intention to use technology: Model development and test. Computers & Education, 57(4), 2432-2440. https://doi.org/10.1016/j.compedu.2011.06.008 DOI: https://doi.org/10.1016/j.compedu.2011.06.008

Teo, T., Sang, G., Mei, B. y Hoi, C. K. W. (2018). Investigating pre-service teachers’ acceptance of Web 2.0 technologies in their future teaching: a Chinese perspective. Interactive Learning Environments, 27(4), 530–546. https://doi.org/10.1080/10494820.2018.1489290 DOI: https://doi.org/10.1080/10494820.2018.1489290

Tondeur, J., Trevisan, O., Howard, S. K. y van Braak, J. (2025). Preparing preservice teachers to teach with digital technologies: An update of effective SQD-strategies. Computers & Education, 232, 105262. https://doi.org/10.1016/J.COMPEDU.2025.105262 DOI: https://doi.org/10.1016/j.compedu.2025.105262

UNESCO. (2023). Guidance for generative AI in education and research. https://doi.org/10.54675/EWZM9535 DOI: https://doi.org/10.54675/EWZM9535

Venkatesh, V. y Davis, F.D. (2000). A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies. Management Science, 46(2), 186-204. https://www.jstor.org/stable/2634758 DOI: https://doi.org/10.1287/mnsc.46.2.186.11926

Venkatesh, V., Thong, J. y Xu, X. (2016). Unified Theory of Acceptance and Use of Technology: A Synthesis and the Road Ahead. Journal of the Association for Information Systems, 17(5),

328-376. https://doi.org/10.17705/1jais.00428 DOI: https://doi.org/10.17705/1jais.00428

Vuorikari, R., Kluzer, S. y Punie, Y. (2022). DigComp 2.2: The Digital Competence Framework for Citizens - With new examples of knowledge, skills and attitudes. Publications Office of the European Union. https://dx.doi.org/10.2760/115376

Wong, G. K. W. (2016). The behavioral intentions of Hong Kong primary teachers in adopting educational technology. Education Tech Research Dev, 64, 313-338. https://doi.org/10.1007/s11423-016-9426-9 DOI: https://doi.org/10.1007/s11423-016-9426-9

Zawacki-Richter, O., Marín, V. I., Bond, M. y Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education – where are the educators? International Journal of Educational Technology in Higher Education, 16, 39. https://doi.org/10.1186/s41239-019-0171-0 DOI: https://doi.org/10.1186/s41239-019-0171-0

Zualkernan, I. (2025). Adoption of Generative AI and Large Language Models in Education: A Short Review. International Conference on Electronics, Information, and Communication (ICEIC), 1-5. https://doi.org/10.1109/ICEIC64972.2025.10879632 DOI: https://doi.org/10.1109/ICEIC64972.2025.10879632